DocumentCode :
1790357
Title :
A framework for real time indoor robot navigation using Monte Carlo Localization and ORB feature detection
Author :
Lye Zhenjun ; Nisar, Humaira ; Malik, A.S.
Author_Institution :
Univ. Tunku Abdul Rahman, Kuala Lumpur, Malaysia
fYear :
2014
fDate :
22-25 June 2014
Firstpage :
1
Lastpage :
2
Abstract :
This paper has introduced a framework for indoor navigation implemented by using a computer, Android device and Lego Mindstorms NXT robot. The Lego Mindstorms NXT robot explores and navigates autonomously through a known environment, making its own decisions. An Android device is used for object recognition. The robot is able to localize itself based on the landmark observed using ORB (oriented fast rotated brief) feature detection and the sensory data from ultrasonic sensor using Monte Carlo Localization. The robot is able to plan its own path towards the goal using the A* shortest path. The navigation system is able to identify and recognize the landmarks and environment; and reacts accordingly to achieve the goal. Experimental results show that the robot navigation system is successfully designed and implemented with an accuracy of ±38 cm root mean squared error.
Keywords :
Android (operating system); Monte Carlo methods; decision making; feature extraction; mean square error methods; mobile robots; navigation; real-time systems; A* shortest path; Android device; Lego Mindstorms NXT robot; Monte Carlo localization; ORB feature detection; decision making; oriented fast rotated brief feature detection; real time indoor robot navigation; root mean squared error; Androids; Computers; Humanoid robots; Monte Carlo methods; Navigation; Robot sensing systems; A∗ algorithm; Monte Carlo localization; feature detection; robot navigation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics (ISCE 2014), The 18th IEEE International Symposium on
Conference_Location :
JeJu Island
Type :
conf
DOI :
10.1109/ISCE.2014.6884401
Filename :
6884401
Link To Document :
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